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economistOver the years our clients have increasingly looked to us to condense results. Their internal stakeholders often only read the executive summary and even then they might only focus on headlines and bold print. Where in the past they might have had time to review hundreds of splits of Max-Diff data or simulations in a conjoint, they now want us to focus our market research reporting on their business question and to answer it as concisely as possible. All of that makes perfect sense. For example, wouldn’t you rather read a headline like “the Eight Richest People in the World Have More Wealth than Half the World’s Population” than endless data tables that lay out all the ways that wealth is unfairly distributed? I know I would…if it were true.

The Economist Magazine did an analysis of the analysis that went into that headline-grabbing statement from Oxfam (a charity). The results indicate a number of flaws that are well worth understanding.

•    They included negative wealth. Some 400 million people have negative wealth (they owe more than they own). So it requires lots of people with very low positive net worth to match the negative wealth of these 400 million people…thus making the overall group much larger than it might have been.    

•    For example, there are 21 million Americans with a net worth of over $350 Billion. Most of them would not be people you might associate with being very poor…rather they have borrowed money to make their lives better now with the plan to pay it off later.

•    They were looking at only material wealth…meaning hard assets like property and cash. Even ignoring wealth like that of George Baily (“The richest man in town!”), each of us possesses wealth in terms of future earning potential. Bill Gates will still have more wealth than a farmer in sub-Saharan Africa, but collectively half the world’s population has a lot of earnings potential.

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2016 election sample representativenessI always dread the inevitable "What do you do?" question. When you tell someone you are in market research you can typically expect a blank stare or a polite nod; so you must be prepared to offer further explanation. Oh, to be a doctor, lawyer or auto mechanic – no explanation necessary!

Of course, as researchers, we grapple with this issue daily, but it is not often we get to hear it played out on major news networks. After one of the debates, I heard Wolf Blitzer on CNN arguing (yes arguing) with one of the campaign strategists about why the online polls being quoted were not "real" scientific polls. Wolf's point was that because the Internet polls being referenced were from a self-selected sample their results were not representative of the population in question (likely voters). Of course, Wolf was correct, and it made me smile to hear this debated on national TV.

A week or so later I heard an even more, in-depth consideration of the same issue. The story was about how the race was breaking down in key swing states. The poll representative went through the results for key states one-by-one. When she discussed Nevada she raised a red flag as to interpreting the poll (which has one candidate ahead by 2 - % points). She further explained it is difficult to obtain a representative sample in Nevada due to a number of factors (odd work hours, transient population, large Spanish speaking population). Her point was that they try to mitigate these issues, but any results must be viewed with a caveat.

Aside from my personal delight that my day-to-day market research concerns are newsworthy, what is the take-away here? For me, it reinforces how important it is to do everything in our power to ensure that for each study our sample is representative. The advent of online data collection, the proliferation of cell phone use and do-it-yourself survey tools may have made the task more difficult, but no less important. When doing sophisticated conjoint, segmentation or max-diff studies, we need to keep in mind that they are only as good as the sample that feeds them.

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  • market research philadelphia farmersA recent post on my Facebook timeline boasted that Lansdale Farmers Market was voted the Best of Montgomery County, PA two years in a row. That’s the market I patronize, and I’d like to feel a bit of pride for it. But I’m a researcher and I know better.

Lansdale Farmers Market is a nice little market in the Philadelphia outskirts, but is it truly the best in the entire county? Possibly, but you can’t tell from this poll. Lansdale Farmers Market solicited my participation by directing me to a site that would register my vote for them (Heaven only knows how much personal information “The Happening List” gains access to).  I’m sure that the other farmers markets solicited their voters in the same or similar ways. This amounts to little more than a popularity contest. Therefore, the only “best” that my market can claim is that it is the best in the county at getting its patrons to vote for it.

But if you have more patrons voting for you, shouldn’t that mean that you truly are the best? Not necessarily. It’s possible that the “best” market serves a smaller geographic area, doesn’t maintain a customer list, or isn’t as good at using social media, to name a few.

  • A legitimate research poll would seek to overcome these biases. So what are the markers of a legitimate research poll? Here are a few:
  1. You’re solicited by a neutral third party. Sometimes the survey sponsors identify themselves up front and that’s okay. But usually if a competitive assessment is being conducted, the sponsor remains anonymous so as not to bias the results.
  2. You’re given competitive choices, not just a plea to “vote for me”.  
  3. You may not be able to tell this, but there should be some attempt to uphold scientific sampling rigor. For example, if the only people included in the farmers market survey were residents of Lansdale, you could see how the sampling method would introduce an insurmountable bias.

The market opens for the summer season in a few weeks, and you can bet that I’ll be there. But I won’t stop to admire the inevitable banner touting their victory.

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Purchase Funnel Measuring AwarenessWe at TRC conduct a lot of choice-based research, with the goal of aligning our studies with real-world decision-making. Lately, though, I’ve been involved in a number of projects in which the primary objective is not to determine choice, but rather awareness. Awareness is the first – and arguably the most critical - part of the purchase funnel. After all, you can’t very well buy or use something if you don’t know it exists. So getting the word out about your brand, a new product or a product enhancement matters.

Awareness research presents several challenges that aren’t necessarily faced in other types of research. Here’s a list of a few items to keep in mind as you embark on an awareness study:

Don’t tip your hand. If you’re measuring awareness of your brand, your ad campaign or one of your products, do not announce at the start of the survey that your company is the sponsor. Otherwise you’ve influenced the very thing you’re trying to measure. You may be required to reveal your identity (if you’re using customer emails to recruit, for example), but you can let participants know up front that you’ll reveal the sponsor at the conclusion of the survey. And do so.

The more surveys the better. Much of awareness research focuses on measuring what happens before and after a specific event or series of events. The most prevalent use of this technique is in ad campaign research. A critical decision factor is how many surveys you should do in each phase. And the answer is, as many as you can afford. The goal is to minimize the margin of error around the results: if your pre-campaign awareness score is 45% and your post-campaign score is 52%, is that a real difference? You can be reasonably assured that it is if you surveyed 500 in each wave, but not if you only surveyed 100. The more participants you survey, the more secure you’ll be that the results are based on real market shifts.

Match your samples. Regardless of how many surveys you do each wave, it’s important that the samples are matched. By that we mean that the make-up of the participants should be as consistent with each other as possible each time you measure. Once again, we want to make certain that results are “real” and aren’t due to methodological choices. You can do this ahead of time by setting quotas, after the fact through weighting, or both. Of course, you can’t control for every single variable. At the very least, you want the key demographics to align.

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I'm a runner and enjoy participating in races. Last May I ran the Delaware Half Marathon and had my worst race ever. What happened? Poor planning. I failed to put together a training plan to prepare me for my race.

This can sometimes happen in Market Research. Poor planning can lead to disastrous results that provide little insight or fail to answer the objectives of the research. Planning is especially important when advanced analytics are used, for example, conjoint that is often used during product development or pricing research. There are many questions to be asked during the planning phase of conjoint design. How should we frame up the exercise? How many features should be evaluated? How many levels for each feature? How many product choices should be presented to a respondent at a time? How should each feature and level be described? Should any prohibitions be used? Sometimes we can lose sight of the research objective amid all the details. A good conjoint plan will keep all parties focused on the end goal. These are all issues I'm contemplating as I design my conjoint exercise (stay tuned for results in my next blog!). I'm taking the time now to properly plan and design my conjoint.

A well thought out plan ensures quality results just as a well thought out running plan ensures a good race! After my half marathon disaster I planned for my next race the same way I would for a conjoint. I considered a number of questions while designing my training plan. How far in advance should I train? How many times a week should I run? Should I enlist a running buddy for the longer runs? My goal was to run a good race. I'm happy to report the planning paid off as I completed the Marine Corps Marathon (my first marathon!) in the time I was hoping for.

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